Publications
Filtered:
Ordered by year and author
2021
Holzinger, A., Weippl, E., Tjoa, A. M., & Kieseberg, P. (2021). Digital Transformation for Sustainable Development Goals (SDGs) - A Security, Safety and Privacy Perspective on AI. In A. Holzinger, P. Kieseberg, A. M. Tjoa, & E. Weippl (Eds.), Machine Learning and Knowledge Extraction (pp. 1–20). Springer International Publishing.
Kieseberg, P., Schrittwieser, S., & Weippl, E. (2021). Secure Internal Data Markets. Future Internet, 13(8). https://doi.org/https://doi.org/10.3390/fi13080208
Neumaier, S., Havur, G., & Pellegrini, T. (2021). Towards an Architecture for Policy-Aware Decentral Dataset Exchange. SEMAPRO 2021, The Fifteenth International Conference on Advances in Semantic Processing. SEMAPRO 2021, The Fifteenth International Conference on Advances in Semantic Processing, Barcelona. https://www.thinkmind.org/index.php?view=article&articleid=semapro_2021_1_40_30020
Pirker, M., & Piller, E. (2021, August 17). Obstacles and Challenges in Transforming Applications for Distributed Data Ledger Integration. Proceedings of the 16th International Workshop on Frontiers in Availability, Reli- Ability and Security (FARES). ARES 2021: The 16th International Conference on Availability, Reliability and Security. https://doi.org/10/gn622r
Priebe, T., Neumaier, S., & Markus, S. (2021). Finding Your Way Through the Jungle of Big Data Architectures. 2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA. https://doi.org/10/gn7mtm
Slijepčević, D., Henzl, M., Klausner, L. D., Dam, T., Kieseberg, P., & Zeppelzauer, M. (2021). k‑Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers. Computers & Security, 111, 19. https://doi.org/10.1016/j.cose.2021.102488
Stöger, K., Schneeberger, D., Kieseberg, P., & Holzinger, A. (2021). Legal aspects of data cleansing in medical AI. Computer Law & Security Review, 42. https://doi.org/https://doi.org/10.1016/j.clsr.2021.105587
2020
Holzinger, A., Kieseberg, P., Tjoa, A. M., & Weippl, E. (2020). Machine Learning and Knowledge Extraction: Fourth IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2020. Springer. https://link.springer.com/book/10.1007/978-3-030-57321-8
Holzinger, A., Kieseberg, P., & Müller, H. (2020). KANDINSKY Patterns: A Swiss-Knife for the Study of Explainable AI. ERCIM-News, 120, 41–42. https://phaidra.fhstp.ac.at/o:4336
König, L., Korobeinikova, Y., Kieseberg, P., & Tjoa, S. (2020). Comparing Blockchain Standards and Recommendations. Future Internet 2020, Future Internet 2020. https://doi.org/10.3390/fi12120222
Longo, L., Goebel, R., Lecue, F., Kieseberg, P., & Holzinger, A. (2020, August 27). Explainable Artificial Intelligence: Concepts, Applications, Research Challenges and Visions. International Cross-Domain Conference for Machine Learning and Knowledge Extraction, Virtuell.
Pellegrini, T., Blomqvist, E., Groth, P., de Boer, V., Alam, M., Käfer, T., Kieseberg, P., Kirrane, S., Meroño-Peñuela, A., & Pandit, H. J. (Eds.). (2020). Semantic Systems. In the Era of Knowledge Graphs: 16th International Conference on Semantic Systems, SEMANTiCS 2020, Amsterdam, The Netherlands, September 7–10, 2020, Proceedings (Vol. 12378). Springer International Publishing. https://doi.org/10.1007/978-3-030-59833-4
Schacht, B., & Kieseberg, P. (2020). An Analysis of 5 Million OpenPGP Keys. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications (JoWUA), 11(3), 107–140. http://isyou.info/jowua/papers/jowua-v11n3-6.pdf
Told, J., & Neumaier, S. (2020). Willensbildung der Kapitalgesellschafter in absentia. Wirtschaftsrechtliche Blätter, 34(7), 361–375. https://doi.org/10/gh38b6
Weber, T., Mitöhner, J., Neumaier, S., & Polleres, A. (2020). ODArchive – Creating an Archive for Structured Data from Open Data Portals. In J. Z. Pan, V. Tamma, C. d"Amato, K. Janowicz, B. Fu, A. Polleres, O. Seneviratne, & L. Kagal (Eds.), The Semantic Web – ISWC 2020 (pp. 311–327). Springer International Publishing. https://doi.org/10/gh38b8
2019
Amiri, F., Quirchmayr, G., Kieseberg, P., Bertone, A., & Weippl, E. (2019). Efficiently Vectorized Anonymization in Data Mining using Genetic Algorithms. Proceedings of the 34th International Conference on ICT Systems Security and Privacy Protection-IFIP SEC 2019.
Holzinger, A., Kieseberg, P., Tjoa, A. M., & Weippl, E. (2019). Machine Learning and Knowledge Extraction: Third IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2019. Springer. https://link.springer.com/book/10.1007/978-3-030-29726-8
Kreimel, P., & Tavolato, P. (2019, December 9). Neural Net-Based Anomaly Detection System in Substation Networks. 6th International Symposium for ICS & SCADA Cyber Security Research, Athen, Griechenland.
Luh, R., Janicke, H., & Schrittwieser, S. (2019). AIDIS: Detecting and classifying anomalous behavior in ubiquitous kernel processes. Computers & Security, 84, 120–147. https://doi.org/10/gh38cc
Luh, R., & Schrittwieser, S. (2019). Advanced threat intelligence: detection and classification of anomalous behavior in system processes. E \& i Elektrotechnik Und Informationstechnik, Springer, 1–7.